S. Umesh

1.3k citations
112 papers · 950 · h-index 17

Impact in

    • Speech and Audio Processing
    • Music and Audio Processing
    • Speech Recognition and Synthesis
    • Natural Language Processing Techniques
    • Speech and dialogue systems

Papers in

    • Speech Recognition and Synthesis 88
    • Natural Language Processing Techniques 10
    • Speech and dialogue systems 8
    • Speech and Audio Processing 80
    • Music and Audio Processing 58
    • Blind Source Separation Techniques 7

S. Umesh

103 papers receiving 863 citations

Peers

S. Umesh
Comparison fields: 5 of 77
  • Signal Processing 637
  • Artificial Intelligence 684
  • Developmental Biology 16
  • Experimental and Cognitive Psychology 88
  • Computer Vision and Pattern Recognition 86
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Citations per year

Countries citing papers authored by S. Umesh

Since Specialization
Citations

This map shows the geographic impact of S. Umesh's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. Umesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Umesh more than expected).

Fields of papers citing papers by S. Umesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. Umesh. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. Umesh. The network helps show where S. Umesh may publish in the future.

Co-authors

The 25 scholars most cited alongside S. Umesh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with S. Umesh Line = papers co-authored together S. Umesh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 112 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199954
2 199653
3 201850
4 201548
5 199948
6 201340
7 200433
8 201327
9 200226
10 202125
11 199323
12 200523
13 200721
14
The development of the Cambridge University RT-04 diarisation system
200421
15 200819
16 200217
17 200217
18 201916
19 200216
20 201815

About S. Umesh

S. Umesh is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Physiology and Experimental and Cognitive Psychology, having authored 112 papers that have together received 950 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (88 papers), Speech and Audio Processing (80 papers), Music and Audio Processing (58 papers), Natural Language Processing Techniques (10 papers), Speech and dialogue systems (8 papers), Blind Source Separation Techniques (7 papers), Advanced Data Compression Techniques (7 papers) and Voice and Speech Disorders (7 papers). The work is most often cited by research in Signal Processing (637 citations), Artificial Intelligence (684 citations), Developmental Biology (16 citations), Experimental and Cognitive Psychology (88 citations) and Computer Vision and Pattern Recognition (86 citations). S. Umesh has collaborated with scholars based in India, United States and Canada. Frequent co-authors include D.J. Nelson, Leon Cohen, D.W. Tufts, Rohit Sinha, K. Sivakumar, Nitin Prasad, Shakti P. Rath, Achintya Kumar Sarkar, Mark Gales and Hermann Ney. Their work appears in journals such as Speech Communication, IEEE/ACM Transactions on Audio Speech and Language Processing, IEEE Transactions on Audio Speech and Language Processing, IEEE Transactions on Signal Processing and IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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